zoukankan html css js c++ java

线程初识

进程: 生产者消费者模型

编程思想，模型，设计模式，理论等等，都是交给你一种编程的方法，以后你遇到类似的情况套用即可
生产者消费者三要素：生产者：产生数据的

消费者：接收数据做进一步处理的

容器：盆（队列）

队列容器作用：缓冲的作用，平衡生产力与消费力，解耦

from multiprocessing import Process
from multiprocessing import Queue
import time
import random

def producer(q,name):
    for i in range(1,6):
        time.sleep(random.randint(1,2))
        res = f'{i}号包子'
        q.put(res)
        print(f'生产者{name}生产了{res}')
def consumer(q,name):
    while 1:
        try:
            food = q.get(timeout=3)
            time.sleep(random.randint(1,3))
            print(f'消费者{name}吃了{food}')
        except Exception:
            return
if __name__ == '__main__':
    q = Queue()
    p1 = Process(target=producer,args=(q,'上约'))
    p2 = Process(target=consumer,args=(q,'海购'))
    p1.start()
    p2.start()

线程的理论知识
1. 什么是线程（一条流水线的工作流程）
  1. 开启一个进程：在内存中开启一个进程空间,然后将主进程的所有的资源数据复制一份,然后调用线程去执行代码
  2. 进程是资源单位，线程是执行单位
2. 线程vs进程
  1. 开启进程的开销非常大,比开启线程的开销大很多.
  2. 开启线程的速度非常快.要快几十倍到上百倍.
  3. 线程线程之间可以共享数据,进程与进程之间需借助队列等方法实现通信.
3. 线程的应用
  1. 并发: 一个cpu 看起来像是同时执行多个任务.
  2. 单个进程开启三个线程.并发的执行任务.
  3. 开启三个进程并发的执行任务.
  4. 开启多线程就非常好了：数据共享, 开销小,速度快.

开启线程的两种方式

第一种：函数的方式

# from threading import Thread
# import time
# def task(name):
#     print(f'{name} is running')
#     time.sleep(1)
#     print(f'{name} is gone')
#
# if __name__ == '__main__':
#     t1 = Thread(target=task,args=('长兴',))
#     t1.start()
#     print('==主线程')

第二种：类的方式
from threading import Thread
import time
class MyThread(Thread):
    def __init__(self,name):
        super().__init__()
        self.name = name
    def run(self):
        print(f'{self.name} is running')
        time.sleep(1)
        print(f'{self.name} is gone')
if __name__ == '__main__':
    t1 = MyThread('长兴')
    t1.start()
    print('===主线程')

线程vs进程的代码对比

开启速度对比

# 多进程
# from threading import Thread
# from multiprocessing import Process
# import os
# def work():
#     print('hello')
# if __name__ == '__main__':
#     t = Process(target=work)
#     t.start()
#     print('主线程/主进程')
永远先执行主进程代码


# 多线程
from threading import Thread
import time
def task(name):
    print(f'{name} is running')
    time.sleep(1)
    print(f'{name} is gone')
if __name__ == '__main__':
    t1 = Thread(target=task,args=('海购',))
    t1.start()
    print('===主线程')

对比pid

# from multiprocessing import Process
# import time
# import os
# def task(name):
#     print(f'子进程:{os.getpid()}')
#     print(f'主进程：{os.getppid()}')
# if __name__ == '__main__':
#     p=Process(target=task,args=('长兴',))
#     p2=Process(target=task,args=('长兴2',))
#     p.start()
#     p2.start()
#     print(f'主进程{os.getpid()}')


# 线程
from threading import Thread
import os
def task():
    print(os.getpid())
if __name__ == '__main__':
    t1 = Thread(target=task)
    t2 = Thread(target=task)
    t1.start()
    t2.start()
    print(f'===主线程{os.getpid()}')
线程没有pid进程号，所求是该线程依赖的进程的pid号

同一个进程内线程共享内部数据

from threading import Thread
import os
x = 3
def task():
    global x
    x = 100
if __name__ == '__main__':
    t = Thread(target=task)
    t.start()
    t.join()
    print(f'==主线程{x}')
同一进程内的资源数据对于这个进程的多个线程来说是共享的

线程的相关其他方法

Thread实例对象的方法
  # isAlive(): 返回线程是否活动的。
  # getName(): 返回线程名。
  # setName(): 设置线程名。

threading模块提供的一些方法：
  # threading.currentThread(): 返回当前的线程变量。
  子线程：<Thread(线程1, started 11252)>
  主线程：<_MainThread(MainThread, started 5256)>
  
  # threading.enumerate(): 返回一个包含正在运行的线程的list。正在运行指线程启动后、结束前，不包括启动前和终止后的线程。
  [<_MainThread(MainThread, started 5256)>]      一个列表
  
  # threading.activeCount(): 返回正在运行的线程数量，len(threading.enumerate())有相同的结果。

from threading import Thread
from threading import currentThread
from threading import enumerate
from threading import activeCount
import os
import time
x = 3
def task():
    print(currentThread())
    time.sleep(1)
    print('666')
print(123)
if __name__ == '__main__':
    t1 = Thread(target=task,name='线程1')
    t2 = Thread(target=task,name='线程2')
    t1.start()
    t2.start()
    time.sleep(2)
    print(t1.isAlive())
    print(t1.getName())
    t1.setName('子线程-1')
    print(t1.name)
    print(currentThread())
    print(enumerate())
    print(activeCount())
    print(f'===主线程{os.getpid()}')

守护线程

# join:阻塞，告知主进程要等待我子进程结束之后，再执行主进程
from threading import Thread
import time
def task(name):
    print(f'{name} is running')
    time.sleep(1)
    print(f'{name} is gone')
if __name__ == '__main__':
    start_time = time.time()
    t1 = Thread(target=task,args=('海购',))
    t2 = Thread(target=task,args=('海购1',))
    t3 = Thread(target=task,args=('海购2',))
    t1.start()
    t1.join()
    t2.start()
    t2.join()
    t3.start()
    t3.join()
    print(f'===主线程{time.time()-start_time}')
    
    ===主线程3.0048482418060303
    
# 守护进程
from multiprocessing import Process
import time
def foo():
    print(123)
    time.sleep(1)
    print('end123')
def bar():
    print(456)
    time.sleep(2)
    print('end456')
if __name__ == '__main__':
    p1 = Process(target=foo,)
    p2 = Process(target=bar,)
    p1.daemon = True
    p1.start()
    p2.start()
    print('==主')
    
    ==主
    456
    end456
    
# 守护线程
from threading import Thread
import time
def sayhi(name):
    print('你滚！')
    time.sleep(2)
    print(f'{name} say hello')
if __name__ == '__main__':
    t = Thread(target=sayhi,args=('长兴',))
    t.daemon = True/t.setdaemon(True)
    t.start()#线程的开启速度要比进程快很多
    print('主线程')
    
    你滚！
    主线程 
-------------------------------------***------------------------------------
from threading import Thread
import time
def foo():
    print(123)
    time.sleep(1)
    print('end123')

def bar():
    print(456)
    time.sleep(3)
    print('end456')
t1 = Thread(target=foo)
t2 = Thread(target=bar)
t1.daemon = True
t1.start()
t2.start()
print('main------')

123
456
main------
end123
end456
主线程什么时候结束？
守护线程	等待	非	守护	子线程以及	主线程结束	之后，结束

from threading import Thread
import time
def foo():
    print(123)
    time.sleep(3)
    print('end123')

def bar():
    print(456)
    time.sleep(1)
    print('end456')
t1 = Thread(target=foo)
t2 = Thread(target=bar)
t1.daemon = True
t1.start()
t2.start()
print('main------')


    123
    456
    main------
    end456

互斥锁

# from threading import Thread
# import time
# import random
# x = 100
#
# def task():
#     time.sleep(random.randint(1,2))
#     global x
#     temp = x
#     time.sleep(random.randint(1, 3))
#     temp = temp - 1
#     x = temp
#
#
# if __name__ == '__main__':
#     l1 = []
#     for i in range(100):
#         t = Thread(target=task)
#         l1.append(t)
#         t.start()
#
#     for i in l1:
#         i.join()
#     print(f'主线程{x}')

# 多个任务公抢一个数据,保证数据的安全的目的,要让其串行


from threading import Thread
from threading import Lock
import time
import random
x = 100

def task(lock):

    lock.acquire()
    # time.sleep(random.randint(1,2))
    global x
    temp = x
    time.sleep(0.01)
    temp = temp - 1
    x = temp
    lock.release()


if __name__ == '__main__':
    mutex = Lock()
    for i in range(100):
        t = Thread(target=task,args=(mutex,))
        t.start()

    time.sleep(3)
   print(f'主线程{x}')

查看全文

相关阅读:
洛谷P3292 [SCOI2016]幸运数字线性基+倍增
 2019牛客暑期多校第五场题解ABGH
暑假集训-8.1总结
 主席树
 2019HDU多校第四场题解
 洛谷P4570 [BJWC2011]元素线性基
 暑假集训-7.31总结
 线性基总结
 Proj. THUIoTFuzz Paper Reading: One Engine to Fuzz 'em All: Generic Language Processor Testing with Semantic Validation
UVALive5876-Writings on the Wall-KMP

原文地址：https://www.cnblogs.com/-777/p/11396476.html